Investigation of various growth mechanisms of solid tumour growth within the linear-quadratic model for radiotherapy

The standard linear-quadratic survival model for radiotherapy is used to investigate different schedules of radiation treatment planning to study how these may be affected by different tumour repopulation kinetics between treatments.

Assessment of the benefits of Discrete Conditional Survival Models in modelling ambulance response times

Many of the challenges faced in health care delivery can be informed through building models. In particular, Discrete Conditional Survival (DCS) models, recently under development, can provide policymakers with a flexible tool to assess time-to-event data. The DCS model is capable of modelling the survival curve based on various underlying distribution types and is capable of clustering or grouping observations (based on other covariate information) external to the distribution fits. The flexibility of the model comes through the choice of data mining techniques that are available in ascertaining the different subsets and also in the choice of distribution types available in modelling these informed subsets. This paper presents an illustrated example of the Discrete Conditional Survival model being deployed to represent ambulance response-times by a fully parameterised model. This model is contrasted against use of a parametric accelerated failure-time model, illustrating the strength and usefulness of Discrete Conditional Survival models.

Linear quadratic and tumour control probability modelling in external beam radiotherapy

The standard linear-quadratic (LQ) survival model for external beam radiotherapy is reviewed with particular emphasis on studying how different schedules of radiation treatment planning may be affected by different tumour repopulation kinetics. The LQ model is further examined in the context of tumour control probability (TCP) models. The application of the Zaider and Minerbo non-Poissonian TCP model incorporating the effect of cellular repopulation is reviewed. In particular the recent development of a cell cycle model within the original Zaider and Minerbo TCP formalism is highlighted. Application of this TCP cell-cycle model in clinical treatment plans is explored and analysed.

Keratinocyte Growth-Factor Promotes Epithelial Survival and Resolution in a Human Model of Lung Injury

Rationale: Increasing epithelial repair and regeneration may hasten resolution of lung injury in patients with the Acute Respiratory Distress Syndrome (ARDS). In animal models of ARDS, Keratinocyte Growth Factor (KGF) reduces injury and increases epithelial proliferation and repair. The effect of KGF in the human alveolus is unknown.

Objectives: To test whether KGF can attenuate alveolar injury in a human model of ARDS.

Methods: Volunteers were randomized to intravenous KGF (60 μg/kg) or placebo for 3 days, before inhaling 50μg lipopolysaccharide. Six hours later, subjects underwent bronchoalveolar lavage (BAL) to quantify markers of alveolar inflammation and cell-specific injury.

Measurements and Main Results: KGF did not alter leukocyte infiltration or markers of permeability in response to LPS. KGF increased BAL concentrations of Surfactant Protein D (SP-D), MMP-9, IL-1Ra, GM-CSF and CRP. In vitro, BAL fluid from KGF-treated subjects (KGF BAL) inhibited pulmonary fibroblast proliferation, but increased alveolar epithelial proliferation. Active MMP-9 increased alveolar epithelial wound repair. Finally, BAL from the KGF pre-treated group enhanced macrophage phagocytic uptake of apoptotic epithelial cells and bacteria compared with BAL from the placebo-treated group. This effect was blocked by inhibiting activation of the GM-CSF receptor.

Conclusions: KGF treatment increases BAL SP-D, a marker of type II alveolar epithelial cell proliferation in a human model of ALI. Additionally KGF increases alveolar concentrations of the anti-inflammatory cytokine IL-1Ra, and mediators that drive epithelial repair (MMP-9) and enhance macrophage clearance of dead cells and bacteria (GM-CSF).

Simulating Coxian Phase-type Distributions for Patient Survival

Coxian phase-type distributions are a special type of Markov model that can be used to represent survival times in terms of phases through which an individual may progress until they eventually leave the system completely. Previous research has considered the Coxian phase-type distribution to be ideal in representing patient survival in hospital. However, problems exist in fitting the distributions. This paper investigates the problems that arise with the fitting process by simulating various Coxian phase-type models for the representation of patient survival and examining the estimated parameter values and eigenvalues obtained. The results indicate that numerical methods previously used for fitting the model parameters do not always converge. An alternative technique is therefore considered. All methods are influenced by the choice of initial parameter values. The investigation uses a data set of 1439 elderly patients and models their survival time, the length of time they spend in a UK hospital.

Out-of-field cell survival following exposure to intensity-modulated radiation fields

PURPOSE:
To determine the in-field and out-of-field cell survival of cells irradiated with either primary field or scattered radiation in the presence and absence of intercellular communication.
METHODS AND MATERIALS:
Cell survival was determined by clonogenic assay in human prostate cancer (DU145) and primary fibroblast (AGO1552) cells following exposure to different field configurations delivered using a 6-MV photon beam produced with a Varian linear accelerator.
RESULTS:
Nonuniform dose distributions were delivered using a multileaf collimator (MLC) in which half of the cell population was shielded. Clonogenic survival in the shielded region was significantly lower than that predicted from the linear quadratic model. In both cell lines, the out-of-field responses appeared to saturate at 40%-50% survival at a scattered dose of 0.70 Gy in DU-145 cells and 0.24 Gy in AGO1522 cells. There was an approximately eightfold difference in the initial slopes of the out-of-field response compared with the a-component of the uniform field response. In contrast, cells in the exposed part of the field showed increased survival. These observations were abrogated by direct physical inhibition of cellular communication and by the addition of the inducible nitric oxide synthase inhibitor aminoguanidine known to inhibit intercellular bystander effects. Additional studies showed the proportion of cells irradiated and dose delivered to the shielded and exposed regions of the field to impact on response.
CONCLUSIONS:
These data demonstrate out-of-field effects as important determinants of cell survival following exposure to modulated irradiation fields with cellular communication between differentially irradiated cell populations playing an important role. Validation of these observations in additional cell models may facilitate the refinement of existing radiobiological models and the observations considered important determinants of cell survival.

Cell survival responses after exposure to modulated radiation fields.

In the present study survival responses were determined in cells with differing radiosensitivity, specifically primary fibroblast (AG0-1522B), human breast cancer (MDA-MB-231), human prostate cancer (DU-145) and human glioma (T98G) cells, after exposure to modulated radiation fields delivered by shielding 50% of the tissue culture flask. A significant decrease (P < 0.05) in cell survival was observed in the shielded area, outside the primary treatment field (out-of-field), that was lower than predicted when compared to uniform exposures fitted to the linear-quadratic model. Cellular radiosensitivity was demonstrated to be an important factor in the level of response for both the in- and out-of-field regions. These responses were shown to be dependent on secretion-mediated intercellular communication, because inhibition of cellular secreted factors between the in- and out-of-field regions abrogated the response. Out-of-field cell survival was shown to increase after pretreatment of cells with agents known to inhibit factors involved in mediating radiation-induced bystander signaling (aminoguanidine, DMSO or cPTIO). These data illustrate a significant decrease in survival out-of-field, dependent upon intercellular communication, in several cell lines with varying radiosensitivity after exposure to a modulated radiation field. This study provides further evidence for the importance of intercellular signaling in modulated exposures, where dose gradients are present, and may inform the refinement of established radiobiological models to facilitate the optimization of advanced radiotherapy treatment plans.

A computational model of cellular response to modulated radiation fields

Purpose:
To develop a model to describe the response of cell populations to spatially modulated radiation exposures of relevance to advanced radiotherapies.

Materials and Methods:
A Monte Carlo model of cellular radiation response was developed. This model incorporated damage from both direct radiation and intercellular communication including bystander signaling. The predictions of this model were compared to previously measured survival curves for a normal human fibroblast line (AGO1522) and prostate tumor cells (DU145) exposed to spatially modulated fields.

Results:
The model was found to be able to accurately reproduce cell survival both in populations which were directly exposed to radiation and those which were outside the primary treatment field. The model predicts that the bystander effect makes a significant contribution to cell killing even in uniformly irradiated cells. The bystander effect contribution varies strongly with dose, falling from a high of 80% at low doses to 25% and 50% at 4 Gy for AGO1522 and DU145 cells, respectively. This was verified using the inducible nitric oxide synthase inhibitor aminoguanidine to inhibit the bystander effect in cells exposed to different doses, which showed significantly larger reductions in cell killing at lower doses.

Conclusions:
The model presented in this work accurately reproduces cell survival following modulated radiation exposures, both in and out of the primary treatment field, by incorporating a bystander component. In addition, the model suggests that the bystander effect is responsible for a significant portion of cell killing in uniformly irradiated cells, 50% and 70% at doses of 2 Gy in AGO1522 and DU145 cells, respectively. This description is a significant departure from accepted radiobiological models and may have a significant impact on optimization of treatment planning approaches if proven to be applicable in vivo.

Discrete Conditional Phase-type model (DC_Ph) for patient waiting time with a logistic regression component to predict patient admission to hospital

Discrete Conditional Phase-type (DC-Ph) models are a family of models which represent skewed survival data conditioned on specific inter-related discrete variables. The survival data is modeled using a Coxian phase-type distribution which is associated with the inter-related variables using a range of possible data mining approaches such as Bayesian networks (BNs), the Naïve Bayes Classification method and classification regression trees. This paper utilizes the Discrete Conditional Phase-type model (DC-Ph) to explore the modeling of patient waiting times in an Accident and Emergency Department of a UK hospital. The resulting DC-Ph model takes on the form of the Coxian phase-type distribution conditioned on the outcome of a logistic regression model.

Autophagy stimulation by rapamycin suppresses lung inflammation and infection by Burkholderia cenocepacia in a model of cystic fibrosis

Cystic fibrosis (CF) is the most common inherited lethal disease in Caucasians which results in multiorgan dysfunction. However, 85% of the deaths are due to pulmonary infections. Infection by Burkholderia cenocepacia (B. cepacia) is a particularly lethal threat to CF patients because it causes severe and persistent lung inflammation and is resistant to nearly all available antibiotics. In CFTR Delta F508 (Delta F508) mouse macrophages, B. cepacia persists in vacuoles that do not fuse with the lysosomes and mediates increased production of IL-1 beta. It is believed that intracellular bacterial survival contributes to the persistence of the bacterium. Here we show for the first time that in wild-type but not in Delta F508 macrophages, many B. cepacia reside in autophagosomes that fuse with lysosomes at later stages of infection. Accordingly, association and intracellular survival of B. cepacia are higher in CFTR-Delta F508 macrophages than in WT macrophages. An autophagosome is a compartment that engulfs nonfunctional organelles and parts of the cytoplasm then delivers them to the lysosome for degradation to produce nutrients during periods of starvation or stress. Furthermore, we show that B. cepacia downregulates autophagy genes in WT and Delta F508 macrophages. However, autophagy dysfunction is more pronounced in Delta F508 macrophages since they already have compromised autophagy activity. We demonstrate that the autophagy-stimulating agent, rapamycin markedly decreases B. cepacia infection in vitro by enhancing the clearance of B. cepacia via induced autophagy. In vivo, rapamycin decreases bacterial burden in the lungs of CF mice and drastically reduces signs of lung inflammation. Together, our studies reveal that if efficiently activated, autophagy can control B. cepacia infection and ameliorate the associated inflammation. Therefore, autophagy is a novel target for new drug development for CF patients to control B. cepacia infection and accompanying inflammation.

Burkholderia cenocepacia requires a periplasmic HtrA protease for growth under thermal and osmotic stress and for survival in vivo

Burkholderia cenocepacia, a member of the B. cepacia complex, is an opportunistic pathogen that causes serious infections in patients with cystic fibrosis. We identified a six-gene cluster in chromosome 1 encoding a two-component regulatory system (BCAL2831 and BCAL2830) and an HtrA protease (BCAL2829) hypothesized to play a role in the B. cenocepacia stress response. Reverse transcriptase PCR analysis of these six genes confirmed they are cotranscribed and comprise an operon. Genes in this operon, including htrA, were insertionally inactivated by recombination with a newly created suicide plasmid, pGPOmegaTp. Genetic analyses and complementation studies revealed that HtrA(BCAL2829) was required for growth of B. cenocepacia upon exposure to osmotic stress (NaCl or KCl) and thermal stress (44 degrees C). In addition, replacement of the serine residue in the active site with alanine (S245A) and deletion of the HtrA(BCAL2829) PDZ domains demonstrated that these areas are required for protein function. HtrA(BCAL2829) also localizes to the periplasmic compartment, as shown by Western blot analysis and a colicin V reporter assay. Using the rat agar bead model of chronic lung infection, we also demonstrated that inactivation of the htrA gene is associated with a bacterial survival defect in vivo. Together, our data demonstrate that HtrA(BCAL2829) is a virulence factor in B. cenocepacia.

The mgtC gene of Burkholderia cenocepacia is required for growth under magnesium limitation conditions and intracellular survival in macrophages

Burkholderia cenocepacia, a bacterium commonly found in the environment, is an important opportunistic pathogen in patients with cystic fibrosis (CF). Very little is known about the mechanisms by which B. cenocepacia causes disease, but chronic infection of the airways in CF patients may be associated, at least in part, with the ability of this bacterium to survive within epithelial cells and macrophages. Survival in macrophages occurs in a membrane-bound compartment that is distinct from the lysosome, suggesting that B. cenocepacia prevents phagolysosomal fusion. In a previous study, we employed signature-tagged mutagenesis and an agar bead model of chronic pulmonary infection in rats to identify B. cenocepacia genes that are required for bacterial survival in vivo. One of the most significantly attenuated mutants had an insertion in the mgtC gene. Here, we show that mgtC is also needed for growth of B. cenocepacia in magnesium-depleted medium and for bacterial survival within murine macrophages. Using fluorescence microscopy, we demonstrated that B. cenocepacia mgtC mutants, unlike the parental isolate, colocalize with the fluorescent acidotropic probe LysoTracker Red. At 4 h postinfection, mgtC mutants expressing monomeric red fluorescent protein cannot retain this protein within the bacterial cytoplasm. Together, these results demonstrate that, unlike the parental strain, an mgtC mutant does not induce a delay in phagolysosomal fusion and the bacterium-containing vacuoles are rapidly targeted to the lysosome, where bacteria are destroyed.